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21 MIT Sloan stories to boost your data analytics strategy

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Data is everywhere, and many companies are looking for their analytics edge — wondering whether they’ve got the right approach and how they can do better.

Some of these stories from MIT Sloan take a close look at broad issues facing business leaders, like how to build or maintain a data culture and a strong data team and how chief data officers can be successful. Others take a closer look at key parts of data analytics strategy, like using unstructured data and external data, and strategies for the era of big data, like data storytelling, data wrapping, and talent analytics.

Where to start: Build a data culture and data team

Startups and newer companies often have an advantage because they’ve built data into the framework of their organizations. Many startups find success when they have information unique to their industry and use analytics to interpret and deploy that data in strategic ways. Here’s a look at how several startups baked analytics into their core business strategy.

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Other companies looking to capitalize on data have to work at overcoming reluctance and changing culture. In this story about how to become a data-driven company, experts focus on creating a data culture, including embracing technology, disrupting the status quo, and incorporating data into every part of the organization.  

Data is the new language of business, and data literacy is one of the keys to building a data-driven company. What does that look like? Experts offer eight steps to boosting data literacy in your company.

Building a data-driven firm takes buy-in from leadership, and most data efforts are led by a chief data officer. Looking to make the business case for chief data officer? Research shows that companies that treat data as a corporate asset and make it central to enterprise business strategy are more likely to reap the benefits of data-driven decision-making.

As digital strategies evolve, the chief data officer role is also changing to focus more on innovation and growth, according to executives. Chief data officers in financial services often face a wide variety of responsibilities and ambiguity as the “new kids on the block” in an organization.  

A chief data officer is just one part of a data department. From data engineers and data scientists to data translators and ontologists, companies are looking to build data analytics dream teams.

And firms aren’t stopping at building teams to use analytics for business goals. Some organizations are also using talent analytics, or people analytics, “a data-driven approach to improving people-related decisions for the purpose of advancing the success of not only the organization but also of individual employees.”

How to use data effectively, from unstructured data to data sharing

Even companies with a robust data strategy should evaluate their programs to make sure they’re making the most of their data. To start, leaders can look to sports teams, which were early adopters of analytics. Their example can help business leaders set a plan for using data in decision-making. 

Unstructured data is an area ripe for growth. A majority of data (80% to 90%, according to estimates) is unstructured information like text, video, audio, web server logs, social media, and more. That locked-away data can be a competitive advantage for firms that figure out how to use it.

Data strategies don’t stop inside the firm — companies have to figure out when and how to incorporate external, or third-party, data. The vast amount of data available, either free to the public or for sale, can add extra insights. For more information about how to share data — within the company or with other organizations — the MIT Center for Information Systems Research offers three best practices for “data sharing 2.0.”

MIT CISR has also researched “data wrapping,” a way to use analytics to make products more valuable for customers.

A skill for the era of big data is data storytelling, or the ability to convey data not just as numbers or figures, but as a narrative that humans can understand. (And check out how to talk to your boss about data.)

A look at companies and industries with the data edge

Several companies and industries are using data to improve productivity, make financial gains, or even as the basis for a business model.

With sensors and improving internet connectivity, forward-looking manufacturing companies are collecting data at every checkpoint, which in turn helps drives automation and new technologies. Here are five supply chain technologies that deliver a competitive advantage.

Industrial data is also fueling a new era of smart and flexible manufacturing. Technology can fuel seamlessly calibrated production, customized goods, and proactively maintained factory floor equipment.

Data is also driving a transformation in real estate as property technology remakes the industry.

Several companies have used data as a core part of their strategy, like the MIT startup that uses data to help design better hospital spaces. A group of MIT graduates has built a real-time data analysis tool for African crop prices, and companies like Etsy have used data about buyers to customize their experience.

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